A review on medical imaging synthesis using deep learning and its clinical applications. Issue 1 (11th December 2020)

• Record Type: Journal Article
• Authors: Wang, Tonghe; Lei, Yang; Fu, Yabo; Wynne, Jacob F.; Curran, Walter J.; Liu, Tian; Yang, Xiaofeng
• Is Part Of: Journal of applied clinical medical physics. Volume 22:Issue 1(2021)
• Page Start: 11
• Page End: 36
• Publication Date: 2020-12-11
• Subjects: CT -- deep learning -- image synthesis -- MRI -- PET -- radiation therapy; Medical physics -- Periodicals; Clinical medicine -- Periodicals; Health Physics; Clinical Medicine; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; 610.153
• DOI: 10.1002/acm2.13121
• Languages: English
• ISSNs: 1526-9914

Abstract

Abstract: This paper reviewed the deep learning‐based studies for medical imaging synthesis and its clinical application. Specifically, we summarized the recent developments of deep learning‐based methods in inter‐ and intra‐modality image synthesis by listing and highlighting the proposed methods, study designs, and reported performances with related clinical applications on representative studies. The challenges among the reviewed studies were then summarized with discussion.